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#' @title lexc_alphaeweibull function
#'
#' @description calculates the instantaneous excess hazard from an exponentiated Weibull distribution
#'
#'
#' @param z_ucured covariates matrix acting on survival function of uncured
#'
#'
#' @param z_pcured covariates matrix acting on cure proportion.
#'
#'
#' @param x the time arguments at which to calculate the cumulative excess hazard
#'
#'
#' @param theta the parameters of the cumulative excess hazard from an exponentiated Weibull distribution
#'
#' @param sign_delta only used for mixture cure rate models to specify if the
#' effects or minus the effects of covariates acting on uncured survival to be
#' considered. Default will be sign_delta = "1". The alternative is
#' sign_delta = "-1".
#'
#'
#' @keywords lexc_alphaeweibull
#'
#' @return An object of class \code{curesurv}.
#' This object is a vector containing:
#'
#' @references Mudholkar, G.S. and Srivastava, D.K. (1993).
#' Exponentiated Weibull family for analyzing bathtub failure-rate data,
#' IEEE Transactions on Reliability, 42, 299-302.
#'
#'
#'
#' Mudholkar, G.S., Srivastava, D.K., and Freimer, M. (1995). The exponentiated
#' Weibull family: a reanalysis of the bus-motor-failure data,
#' Technometrics, 37, 436–445.doi:10.2307/1269735
#' (\href{https://www.jstor.org/stable/1269735}{jstor})
#'
#'
#' @keywords internal
lexc_alphaeweibull <- function(z_ucured = z_ucured, z_pcured = z_pcured,
x = x, theta = theta, sign_delta = 1) {
n_z_pcured <- ncol(z_pcured)
n_z_ucured <- ncol(z_ucured)
if (n_z_pcured > 0 & n_z_ucured > 0 ) {
beta0 <- theta[1]
betak <- theta[2:(1 + n_z_pcured)]
lambda <- theta[(1 + n_z_pcured + 1)]
gamma <- theta[(1 + n_z_pcured + 2)]
thetapw <- theta[(1 + n_z_pcured + 3)]
delta <-sign_delta*theta[(1 + n_z_pcured + 4):(1 + n_z_pcured + 3 + n_z_ucured)]
pcure <- beta0 + z_pcured %*% betak
cured <- 1/(1 + exp(-pcure))
usurv <- (1 - (1 - exp(-(exp(lambda+z_ucured %*% delta) * x) ^ exp(gamma))) ^ exp(thetapw))
u_f <-exp(gamma) * exp(thetapw) * exp(lambda+z_ucured %*% delta) *
(1 - exp(-(exp(lambda+z_ucured %*% delta) * x ) ^ exp(gamma))) ^ (exp(thetapw) - 1) *
exp(-(exp(lambda+z_ucured %*% delta) * x) ^ exp(gamma)) *
(exp(lambda+z_ucured %*% delta)*x) ^ (exp(gamma) - 1)
uhaz <- u_f/usurv
SurvE <- cured + (1 - cured)*usurv
cumHazE <- -log(SurvE)
ehaz <- ((1 - cured)*u_f) / (cured + (1 - cured)*usurv)
} else if (n_z_pcured == 0 & n_z_ucured > 0 ) {
beta0 <- theta[1]
lambda <- theta[(1 + n_z_pcured + 1)]
gamma <- theta[(1 + n_z_pcured + 2)]
thetapw <- theta[(1 + n_z_pcured + 3)]
delta <-sign_delta*theta[(1 + n_z_pcured + 4):(1 + n_z_pcured + 3 + n_z_ucured)]
pcure <- beta0
cured <- 1/(1 + exp(-pcure))
usurv <- (1 - (1 - exp(-(exp(lambda+z_ucured %*% delta) * x) ^ exp(gamma))) ^ exp(thetapw))
u_f <-exp(gamma) * exp(thetapw) * exp(lambda+z_ucured %*% delta) *
(1 - exp(-(exp(lambda+z_ucured %*% delta) * x ) ^ exp(gamma))) ^ (exp(thetapw) - 1) *
exp(-(exp(lambda+z_ucured %*% delta) * x) ^ exp(gamma)) *
(exp(lambda+z_ucured %*% delta)*x) ^ (exp(gamma) - 1)
uhaz <- u_f/usurv
SurvE <- cured + (1 - cured)*usurv
cumHazE <- -log(SurvE)
ehaz <- ((1 - cured)*u_f) / (cured + (1 - cured)*usurv)
} else if (n_z_pcured > 0 & n_z_ucured == 0 ) {
beta0 <- theta[1]
betak <- theta[2:(1 + n_z_pcured)]
lambda <- theta[(1 + n_z_pcured + 1)]
gamma <- theta[(1 + n_z_pcured + 2)]
thetapw <- theta[(1 + n_z_pcured + 3)]
pcure <- beta0 + z_pcured %*% betak
cured <- 1/(1 + exp(-pcure))
usurv <- (1 - (1 - exp(-(exp(lambda) * x) ^ exp(gamma))) ^ exp(thetapw))
u_f <-exp(gamma) * exp(thetapw) * exp(lambda) *
(1 - exp(-(exp(lambda) * x ) ^ exp(gamma))) ^ (exp(thetapw) - 1) *
exp(-(exp(lambda) * x) ^ exp(gamma)) *
(exp(lambda)*x) ^ (exp(gamma) - 1)
uhaz <- u_f/usurv
SurvE <- cured + (1 - cured)*usurv
cumHazE <- -log(SurvE)
ehaz <- ((1 - cured)*u_f) / (cured + (1 - cured)*usurv)
} else if (n_z_pcured == 0 & n_z_ucured == 0 ) {
beta0 <- theta[1]
lambda <- theta[2]
gamma <- theta[3]
thetapw <- theta[4]
pcure <- beta0
cured <- 1/(1 + exp(-pcure))
usurv <- (1 - (1 - exp(-(exp(lambda) * x)^exp(gamma)))^exp(thetapw))
u_f <-exp(gamma) * exp(thetapw) * exp(lambda) *
(1 - exp(-(exp(lambda) * x ) ^ exp(gamma))) ^ (exp(thetapw) - 1) *
exp(-(exp(lambda) * x) ^ exp(gamma)) *
(exp(lambda)*x) ^ (exp(gamma) - 1)
uhaz <- u_f/usurv
SurvE <- cured + (1 - cured)*usurv
cumHazE <- -log(SurvE)
ehaz <- ((1 - cured)*u_f) / (cured + (1 - cured)*usurv)
}
return(ehaz)
}
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